Kaggle Competitions

Selected solutions from my Kaggle machine learning competitions.

Mitsui & Co. Commodity Prediction Challenge

Task: Predict 424 commodity spread targets using time-series modeling.

Approach:

• Time-series ensemble combining LightGBM, XGBoost, and CatBoost
• Lag features and rolling statistics for temporal patterns
• Per-target Ridge regression blending
• 6-fold time-series cross-validation
• Optimized for Sharpe-like rank correlation metric

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